


'''simple docstring'''



import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer


__A						=logging.get_logger(__name__)

__A						={"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__A						={
    "vocab_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt"
        ),
        "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt",
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli": (
            "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/tokenizer.json"
        ),
    },
}

__A						={
    "squeezebert/squeezebert-uncased": 5_12,
    "squeezebert/squeezebert-mnli": 5_12,
    "squeezebert/squeezebert-mnli-headless": 5_12,
}


__A						={
    "squeezebert/squeezebert-uncased": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True},
}


class 		_snake_case       (  _SCREAMING_SNAKE_CASE						):
					lowerCAmelCase   :int				=       VOCAB_FILES_NAMES
					lowerCAmelCase   :Optional[Any]				=       PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase   :str				=       PRETRAINED_INIT_CONFIGURATION
					lowerCAmelCase   :List[Any]				=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase   :Tuple				=       SqueezeBertTokenizer




					def __init__(   self				,				_lowerCamelCase=None				,				_lowerCamelCase=None				,				_lowerCamelCase=True				,				_lowerCamelCase="[UNK]"				,				_lowerCamelCase="[SEP]"				,				_lowerCamelCase="[PAD]"				,				_lowerCamelCase="[CLS]"				,				_lowerCamelCase="[MASK]"				,				_lowerCamelCase=True				,				_lowerCamelCase=None				,				**_lowerCamelCase				,				):
								super().__init__(
								    __UpperCAmelCase				,				tokenizer_file=__UpperCAmelCase				,				do_lower_case=__UpperCAmelCase				,				unk_token=__UpperCAmelCase				,				sep_token=__UpperCAmelCase				,				pad_token=__UpperCAmelCase				,				cls_token=__UpperCAmelCase				,				mask_token=__UpperCAmelCase				,				tokenize_chinese_chars=__UpperCAmelCase				,				strip_accents=__UpperCAmelCase				,				**__UpperCAmelCase				,				)

								UpperCAmelCase__	:       Optional[int]   =  json.loads(self.backend_tokenizer.normalizer.__getstate__())
								if (
								    normalizer_state.get("""lowercase"""				,				__UpperCAmelCase) != do_lower_case
								    or normalizer_state.get("""strip_accents"""				,				__UpperCAmelCase) != strip_accents
								    or normalizer_state.get("""handle_chinese_chars"""				,				__UpperCAmelCase) != tokenize_chinese_chars
								):
											UpperCAmelCase__	:       Any   =  getattr(__UpperCAmelCase				,				normalizer_state.pop("""type"""))
											UpperCAmelCase__	:       List[Any]   =  do_lower_case
											UpperCAmelCase__	:       Optional[int]   =  strip_accents
											UpperCAmelCase__	:       Any   =  tokenize_chinese_chars
											UpperCAmelCase__	:       str   =  normalizer_class(**__UpperCAmelCase)

								UpperCAmelCase__	:       Union[str, Any]   =  do_lower_case




					def 					snake_case__    (   self				,				_lowerCamelCase				,				_lowerCamelCase=None):
								UpperCAmelCase__	:       str   =  [self.cls_token_id] + token_ids_a + [self.sep_token_id]

								if token_ids_a:
											output += token_ids_a + [self.sep_token_id]

								return output




					def 					snake_case__    (   self				,				_lowerCamelCase				,				_lowerCamelCase = None):
								UpperCAmelCase__	:       List[Any]   =  [self.sep_token_id]
								UpperCAmelCase__	:       Optional[int]   =  [self.cls_token_id]
								if token_ids_a is None:
											return len(cls + token_ids_a + sep) * [0]
								return len(cls + token_ids_a + sep) * [0] + len(token_ids_a + sep) * [1]




					def 					snake_case__    (   self				,				_lowerCamelCase				,				_lowerCamelCase = None):
								UpperCAmelCase__	:       str   =  self._tokenizer.model.save(__UpperCAmelCase				,				name=__UpperCAmelCase)
								return tuple(__UpperCAmelCase)


import string
from math import logaa






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_		):
							A      :					List[str]      		=					document.translate(
							    str.maketrans(''''''     ,				''''''     ,				string.punctuation		)		).replace('''\n'''     ,				''''''		)
							A      :					Optional[int]      		=					document_without_punctuation.split(''' '''		)  # word tokenization
							return len([word for word in tokenize_document if word.lower() == term.lower()]		)






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_		):
							A      :					Dict      		=					corpus.lower().translate(
							    str.maketrans(''''''     ,				''''''     ,				string.punctuation		)		)  # strip all punctuation and replace it with ''
							A      :					Dict      		=					corpus_without_punctuation.split('''\n'''		)
							A      :					List[Any]      		=					term.lower()
							return (len([doc for doc in docs if term in doc]		), len(lowerCamelCase_		))






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_=False		):
							if smoothing:
														if n == 0:
																					raise ValueError('''log10(0) is undefined.'''		)
														return round(1 + logaa(n / (1 + df)		)     ,				3		)

							if df == 0:
														raise ZeroDivisionError('''df must be > 0'''		)
							elif n == 0:
														raise ValueError('''log10(0) is undefined.'''		)
							return round(logaa(n / df		)     ,				3		)






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_		):
							return round(tf * idf     ,				3		)






